In this study, poly(N-isopropylacrylamide-co-2-hydroxypropyl methacrylate) hydrogels were synthesized using free radical initiated copolymerization method. Four hydrogels with different cross-linker concentrations were prepared. Semi-crystalline, cross-linked copolymer networks were confirmed by FTIR, SEM and XRD analysis. Variation of swelling behaviour was monitored gravimetrically and thermo-responsiveness has been noticed. An application of synthesized thermo-responsive hydrogels as carriers for the modulated release of anti-inflammatory model drug was investigated. Moreover, naproxen loading into these hydrogels was also determined using FTIR, SEM and XRD techniques and release was analyzed using HPLC method at simulated physiological conditions. Swelling kinetic and mechanism of water transport, as well as diffusion of naproxen through the hydrogels were analyzed. Thus, the aim of this work was to study various compositions of obtained hydrogels and their possibility of application as a thermo-responsive carrier for prolonged naproxen release in order to evaluate as a potential candidate for drug carrier in future pharmaceutical applications.

The potato cyst nematode (PCN) Globodera rostochiensis is a plant parasite of potato classified into a group of quarantine organisms causing high economic losses worldwide. Due to the long persistence of the parasite in soil, cysts harbor numerous bacteria whose presence can lead to cyst death and population decline. The cysts of G. rostochiensis found in two potato fields were used as a source of bacteria. The universal procedure was applied to extract DNA from bacteria which was then sequenced with 16S primers. The aims of the study were to identify bacterial microbiota associated with the PCN populations and to infer their phylogenetic relationships based on the maximum likelihood and Bayesian phylogeny of the 16S sequences. In addition, the impact of the most significant climate and edaphic factors on bacterial diversity were evaluated. Regarding the higher taxonomy, our results indicate that the prevalent bacterial classes were Bacilli, Actinobacteria and Alphaproteobacteria. Phylogenetic analyses clustered Brevibacterium frigoritolerans within the family Bacillaceae, confirming its recent reclassification. Long-term climate factors, such as air temperature, insolation hours, humidity and precipitation, as well as the content of soil organic matter, affected the bacterial diversity. The ability of cyst nematodes to persist in soil for a long time qualifies them as a significant natural source to explore the soil bacterial microbiota.

Essential oils (EOs) have historically been used for centuries in folk medicine, and nowadays they seem to be a promising control strategy against wide spectra of pathogens, diseases, and parasites. Studies on free-living nematodes are scarce. The free-living microbivorous nematode Panagrolaimus sp. was chosen as the test organism. The nematode possesses extraordinary biological properties, such as resistance to extremely low temperatures and long-term survival under minimal metabolic activity. Fifty EOs from 22 plant families of gymnosperms and angiosperms were tested on Panagrolaimus sp. The aims of this study were to investigate the in vitro impact of EOs on the psychrophilic nematode Panagrolaimus sp. in a direct contact bioassay, to list the activity of EOs based on median lethal concentration (LC50), to determine the composition of the EOs with the best nematicidal activity, and to compare the activity of EOs on Panagrolaimus sp. versus plant parasitic nematodes. The results based on the LC50 values, calculated using Probit analysis, categorized the EOs into three categories: low, moderate and highly active. The members of the laurel family, i.e., Cinnamomum cassia and C. burmannii, exhibited the best nematicidal activity. Aldehydes were generally the major chemical components of the most active EOs and were the chemicals potentially responsible for the nematicidal activity.

Cereals, particularly wheat, are staple food of the people from the Balkans, dating back to the Neolithic age. In Serbia, cereals are predominantly grown in its northern part between 44° and 45.5° N of the Pannonian Plain. One of the most economically important nematodes on wheat is the cereal cyst nematode, Heterodera filipjevi. Cysts of H. filipjevi survive in soil for years and shelter a large number of microorganisms. The aims of this study were to investigate the diversity of mycobiota associated with the cereal cyst nematode H. filipjevi, to infer phylogenetic relationships of the found mycobiota, and to explore the ecological connection between fungi and the field history, including the potential of fungi in bioremediation and the production of novel bioactive compounds. Cysts were isolated from soil samples with a Spears apparatus and collected on a 150-µm sieve. The cysts were placed on potato dextrose agar, and maintained for two weeks at 27°C. Following fungal isolation and colony growing, the fungal DNA was extracted, the ITS region was amplified, and PCR products were sequenced. The study showed that the isolated fungal species belong to diverse phyla, including Ascomycota, Basidiomycota, and Mucoromycota. Ascomycota is represented by the families Clavicipitaceae, Sarocladiaceae, Nectriaceae, and Phaeosphaeriaceae. Basidiomycota is represented by the families Cerrenaceae, Polyporaceae, Phanerochaetaceae, and Meruliaceae, and the order Cantharellales. The family Mortierellaceae represents Mucoromycota. The members of Ascomycota and Basidiomycota both depict the field history. Ascomycota indicate the fungal infection is of recent origin, while Basidiomycota point toward the preceding host plants, enabling the plant field colonization history to be traced chronologically.

In the face of increasing climate variability, understanding the dynamics of plant-to-plant interactions within crops is becoming increasingly important. This study aimed to examine plant responses to varying intensities of inter-plant competition, induced bz different planting densities, to enhance the accuracy of future yield prediction models. Six hybrids were grown at three planting densities (S1, S4, S7). Grain yield and yield components were estimated at four developmental points during grain filling (V1 to V4). These regression models and machine learning (ML) were applied to predict maize production under variable weather conditions. The factor year was the main source of variability, with less favourable conditions in the second year (G2) reducing yield by approximately 1–2%. Lower planting density (S1) improved individual plant development and yield components, while maximum density (S7) resulted in higher grain yield despite reduced individual performance. Hybrid H5 showed strong tolerance to high density, producing the highest yield under S7 conditions. Machine learning models accurately predicted key seed quality traits—moisture, oil, and protein—with performance metrics exceeding 80% accuracy. Specifically, R² values reached 0.82 for moisture content and 0.77 for oil concentration, indicating strong predictive capability. These findings support careful selection of hybrids and optimal planting density strategies in future cropping systems to increase yield and maintain seed quality in different environments.